Daughters of depressed mothers are at extremely high risk (HR) for developing major depressive disorder (MDD) by early adulthood. To develop more targeted, mechanistic prevention efforts for this HR population, it is essential to clarify the familial mechanisms implicated in this risk. Prior studies suggest that a dysfunctional neural circuit characterizes HR offspring during negative social-emotional and motivational processing. Despite replicable findings documenting this effect, it is not clear whether disrupted neural circuit activation among HR offspring mirrors that of their depressed mothers, representing a neural signature of depression risk that is transmitted from the mother to the daughter. It is also largely unknown if and how this neural signature relates to reactivity and regulation of affect in the real world, which is key to understanding its clinical significance and identifying brain-behavior targets for prevention and intervention. In the current K23 application, the candidate proposes to examine neurobehavioral markers of social-emotional and motivational processing in a sample of 40 mothers with a history of recurrent MDD (rMDD) and their non-MDD, HR daughters (ages 13-16), and 40 mothers with no history of psychopathology and their non-MDD, low risk (LR) daughters. By combining neural and behavioral measures with a longitudinal design, the candidate will test whether neural regions implicated in negative social- emotional and motivational processing (a) differentiate HR from LR dyads and are concordant between mothers and their daughters, representing a familial risk marker, (b) are predictive of offspring?s behavioral ratings of affective processing outside of the laboratory using Ecological Momentary Assessment (EMA), and (c) are associated with the trajectory of offspring?s depressive symptoms over a multi-wave follow-up. In the current proposal, the candidate seeks to build upon her strong foundation in multiple levels of analysis to study affective processing and youth depression risk by gaining additional training in three new domains: 1) Developmental affective neuroscience and functional magnetic resonance imaging (fMRI) methodology, 2) Ecological momentary assessment (EMA), and 3) Advanced statistical modeling for nested, multi-method, longitudinal data. The Department of Psychiatry at the University of Illinois at Chicago is an outstanding environment in which to engage in interdisciplinary training. The candidate's mentorship team (Drs. Phan, Keenan, and Mermelstein) and consultant team (Drs. Hedeker and Gotlib) have extensive experience in developmental affective neuroscience methods (including fMRI), longitudinal high risk designs, use of EMA methods, and statistical expertise in multilevel and longitudinal analyses. The proposed study will inform the design of larger R01 studies examining whether neural and behavioral mechanisms of risk can be altered to prevent the development of depression in HR offspring. This study coupled with completion of the identified training goals will effectively propel the candidate towards establishing an independent program of research focused on identifying behavioral-brain risk phenotypes and preventative interventions for youth depression.